{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 项目：分析鸢尾花种类数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析目标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此数据分析报告的目的是基于鸢尾花的属性数据，分析两种鸢尾花萼片、花瓣的长度和宽度平均值，是否存在显著性差异，让我们可以对不同种类鸢尾花的属性特征进行推断。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 简介"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原始数据`Iris.csv`包括两种鸢尾花，每种有 50 个样本，以及每个样本的一些属性，包括萼片的长度和宽度、花瓣的长度和宽度。\n",
    "\n",
    "`Iris.csv`每列的含义如下：\n",
    "- Id：样本的ID。\n",
    "- SepalLengthCm：萼片的长度（单位为厘米）。\n",
    "- SepalWidthCm：萼片的宽度（单位为厘米）。\n",
    "- PetalLengthCm：花瓣的长度（单位为厘米）。\n",
    "- PetalWidthCm：花瓣的宽度（单位为厘米）。\n",
    "- Species：鸢尾花种类。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "导入数据分析所需要的库，并通过Pandas的`read_csv`函数，将原始数据文件`Iris.csv`里的数据内容，解析为DataFrame并赋值给变量`original_data`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "original_data = pd.read_csv(\"Iris.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0   1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1   2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2   3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3   4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4   5            5.0           3.6            1.4           0.2  Iris-setosa"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "original_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 评估和清理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在这一部分中，我们将对在上一部分建立的`original_data`DataFrame所包含的数据进行评估和清理。\n",
    "\n",
    "主要从两个方面进行：结构和内容，即整齐度和干净度。\n",
    "\n",
    "数据的结构性问题指不符合“每个变量为一列，每个观察值为一行，每种类型的观察单位为一个表格”这三个标准；数据的内容性问题包括存在丢失数据、重复数据、无效数据等。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了区分开经过清理的数据和原始的数据，我们创建新的变量`cleaned_data`，让它为`original_data`复制出的副本。我们之后的清理步骤都将被运用在`cleaned_data`上。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cleaned_data = original_data.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据整齐度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0   1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1   2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2   3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3   4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4   5            5.0           3.6            1.4           0.2  Iris-setosa\n",
       "5   6            5.4           3.9            1.7           0.4  Iris-setosa\n",
       "6   7            4.6           3.4            1.4           0.3  Iris-setosa\n",
       "7   8            5.0           3.4            1.5           0.2  Iris-setosa\n",
       "8   9            4.4           2.9            1.4           0.2  Iris-setosa\n",
       "9  10            4.9           3.1            1.5           0.1  Iris-setosa"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从头部的10行数据来看，数据符合“每个变量为一列，每个观察值为一行，每种类型的观察单位为一个表格”，因此不存在结构性问题。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据干净度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来通过`info`，对数据内容进行大致了解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 100 entries, 0 to 99\n",
      "Data columns (total 6 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Id             100 non-null    int64  \n",
      " 1   SepalLengthCm  100 non-null    float64\n",
      " 2   SepalWidthCm   100 non-null    float64\n",
      " 3   PetalLengthCm  100 non-null    float64\n",
      " 4   PetalWidthCm   100 non-null    float64\n",
      " 5   Species        100 non-null    object \n",
      "dtypes: float64(4), int64(1), object(1)\n",
      "memory usage: 4.8+ KB\n"
     ]
    }
   ],
   "source": [
    "cleaned_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从输出结果来看，`cleaned_data`数据共有100条观察值，不存在缺失值。\n",
    "\n",
    "`Id`表示样本ID，数据类型不应为数字，应为字符串，所以需要进行数据格式转换。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       2\n",
       "2       3\n",
       "3       4\n",
       "4       5\n",
       "     ... \n",
       "95     96\n",
       "96     97\n",
       "97     98\n",
       "98     99\n",
       "99    100\n",
       "Name: Id, Length: 100, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Id\"] = cleaned_data[\"Id\"].astype(\"str\")\n",
    "cleaned_data[\"Id\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理缺失数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从`info`方法的输出结果来看，`cleaned_data`不存在缺失值，因此不需要对缺失数据进行处理。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理重复数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据数据变量的含义以及内容来看，`cleaned_data`里的`Id`是样本的唯一标识符，不应该存在重复，因此查看是否存在重复值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Id\"].duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "输出结果为0，说明不存在重复值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理不一致数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不一致数据可能存在于`Species`变量中，我们要查看是否存在多个不同值指代同一鸢尾花种类的情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Species\n",
       "Iris-setosa        50\n",
       "Iris-versicolor    50\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Species\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上输出结果来看，`Species`只有两种可能的值，`Iris-versicolor`和`Iris-setosa`，不存在不一致数据。\n",
    "\n",
    "我们可以把这列的类型转换为`Category`，好处是比字符串类型更节约内存空间，也能表明说值的类型有限。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Iris-setosa\n",
       "1         Iris-setosa\n",
       "2         Iris-setosa\n",
       "3         Iris-setosa\n",
       "4         Iris-setosa\n",
       "           ...       \n",
       "95    Iris-versicolor\n",
       "96    Iris-versicolor\n",
       "97    Iris-versicolor\n",
       "98    Iris-versicolor\n",
       "99    Iris-versicolor\n",
       "Name: Species, Length: 100, dtype: category\n",
       "Categories (2, object): ['Iris-setosa', 'Iris-versicolor']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Species\"] = cleaned_data[\"Species\"].astype(\"category\")\n",
    "cleaned_data[\"Species\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理无效或错误数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以通过DataFrame的`describe`方法，对数值统计信息进行快速了解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.471000</td>\n",
       "      <td>3.094000</td>\n",
       "      <td>2.862000</td>\n",
       "      <td>0.785000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.641698</td>\n",
       "      <td>0.476057</td>\n",
       "      <td>1.448565</td>\n",
       "      <td>0.566288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.400000</td>\n",
       "      <td>3.050000</td>\n",
       "      <td>2.450000</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.900000</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>4.325000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm\n",
       "count     100.000000    100.000000     100.000000    100.000000\n",
       "mean        5.471000      3.094000       2.862000      0.785000\n",
       "std         0.641698      0.476057       1.448565      0.566288\n",
       "min         4.300000      2.000000       1.000000      0.100000\n",
       "25%         5.000000      2.800000       1.500000      0.200000\n",
       "50%         5.400000      3.050000       2.450000      0.800000\n",
       "75%         5.900000      3.400000       4.325000      1.300000\n",
       "max         7.000000      4.400000       5.100000      1.800000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上统计信息来看，`cleaned_data`里不存在脱离现实意义的数值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 整理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对数据的整理，与分析方向紧密相关。此次数据分析目标是，基于鸢尾花的属性数据，分析两种鸢尾花萼片、花瓣的长度和宽度平均值，是否存在显著性差异。\n",
    "\n",
    "那么我们可以对数据基于`Species`列，先把各个鸢尾花种类样本数据筛选出来。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0  1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1  2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2  3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3  4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4  5            5.0           3.6            1.4           0.2  Iris-setosa"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_setosa = cleaned_data.query('Species == \"Iris-setosa\"')\n",
    "iris_setosa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(iris_setosa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.4</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>6.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>6.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>5.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm  \\\n",
       "50  51            7.0           3.2            4.7           1.4   \n",
       "51  52            6.4           3.2            4.5           1.5   \n",
       "52  53            6.9           3.1            4.9           1.5   \n",
       "53  54            5.5           2.3            4.0           1.3   \n",
       "54  55            6.5           2.8            4.6           1.5   \n",
       "\n",
       "            Species  \n",
       "50  Iris-versicolor  \n",
       "51  Iris-versicolor  \n",
       "52  Iris-versicolor  \n",
       "53  Iris-versicolor  \n",
       "54  Iris-versicolor  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_versicolor = cleaned_data.query('Species == \"Iris-versicolor\"')\n",
    "iris_versicolor.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(iris_versicolor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 探索数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在着手推断统计学分析之前，我们可以先借助数据可视化，探索`Setosa`和`Versicolor`这两种鸢尾花的变量特点。\n",
    "\n",
    "可视化探索可以帮我们对数据有一个更直观的理解，比如了解数据的分布、发现变量之间的关系，等等，从而为后续的进一步分析提供方向。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "针对数值，我们可以直接绘制成对图，利用其中的密度图查看不同变量的分布，以及利用散点图了解变量之间的关系。\n",
    "\n",
    "并且，由于此次分析目的是了解不同种类鸢尾花的属性特征是否存在差异，我们可以利用颜色对图表上不种类类的样本进行分类。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1143x1000 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(cleaned_data, hue=\"Species\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上可以看出，`Setosa`和`Versicolor`样本的花瓣长度以及花瓣宽度的分布存在明显数值上的不同，已经可以猜测假设检验的结果是，两种鸢尾花的花瓣长度与宽度有统计显著性差异。\n",
    "\n",
    "萼片的长度和宽度在分布上存在重叠，暂时无法仅通过图表下结论，需要进行假设检验，来推断总体的萼片长度和宽度之间是否有差异。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将利用假设检验，依次检验`Setosa`和`Versicolor`这两种鸢尾花在萼片、花瓣的长度和宽度平均值方面，是否存在统计显著性差异。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只有样本数据，不知道总体的标准差，加上两组样本数各为50，样本数量不大，因此进行t检验，而不是z检验。假设此数据集样本符合t检验的两个前提：样本为随机抽样，总体呈正态分布。\n",
    "\n",
    "我们先引入t检验所需要的模块。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析萼片长度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 萼片长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['SepalLengthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['SepalLengthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的萼片更长，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-10.52098626754911\n",
      "p值：8.985235037487079e-18\n"
     ]
    }
   ],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"SepalLengthCm\"], iris_versicolor[\"SepalLengthCm\"])\n",
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析萼片宽度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 萼片长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PVVRUaM6cObrjjjtsCwcAAFCfBv2K9S9/+Uu9+eabuv766/XII48oLS1NkrRnzx4tWrRI1dXVeuqppxolKAAAwPc1qMR069ZNmzdv1kMPPaTZs2fLsixJksvl0rhx47Ro0SJ169atUYICAAB8X4Pf7K5nz5567733dPr0ae3fv1+WZalPnz7q2LFjY+QDAACoU1Dv2CtJHTt21JAhQ+zMAgAAcNWC+uwkAAAAp1FiAACAkZpNiXn++eflcrk0Y8YMp6MAAAADNIsSs23bNi1dulQDBgxwOgoAADBE0Bf22qWsrEyTJk3S7373Oz3zzDOX3dfv98vv9wfu+3y+xo6Hq+R2u+X1em2ZlZCQoJSUFFtmAWg4vp9hCsdLzLRp0zRhwgSNGTPmiiVm/vz5mjt3bhMlw9Vyu93KSE9TecWl7+QcjHbRUSrcs5e/+AAHuN1upadnqKKi3JZ50dHttGdPId/PaBSOlpjVq1drx44d2rZt21XtP3v2bM2cOTNw3+fzKTk5ubHi4Sp5vV6VV1Tq9QcGKiMpJqRZhZ4yZS3Ll9fr5S89wAFer1cVFeUaet8cxSWlhjTL5zmoz5fP5fsZjcaxEnP48GE99thjWrdunaKioq7qOZGRkYqMjGzkZAhWRlKMBqXGOx0DgA3iklLVKSXN6RjAZTlWYvLy8lRcXKxBgwYFtlVXV2vTpk169dVX5ff71aZNG6fiAQCAZs6xEnPrrbdq165dtbZNmTJF6enpeuKJJygwAADgshwrMbGxsbrhhhtqbWvfvr06d+58yXYAAICLNYv3iQEAAGgox3/F+vtyc3OdjgAAAAzBmRgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACNRYgAAgJEoMQAAwEiUGAAAYCRKDAAAMBIlBgAAGIkSAwAAjESJAQAARqLEAAAAI1FiAACAkSgxAADASJQYAABgJEoMAAAwEiUGAAAYiRIDAACMRIkBAABGosQAAAAjUWIAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACOFOx0AziosLGwWM+ye2RiZWoPyU8d0yr036Oef9XokSWXFbp1q3y6kLD7PwZCe39q43W55vd6Q5/C9A5NQYlopT0mlwiRlZWXZNtN/zh/yDLtz2ZGpNfCWVSlM0r61r2nf2tdCmhUmKX/VC7bkCpPk8XhsmdWSud1upadnqKKi3LaZ5/3nbJsFNBZKTCt1prxKNZJ+NzlNg67tEtKs93YVK+fNfaqqqmo2uezM1BqU+qtVI2nehCSl9+wW9JwNu45o8ScnQp4jSd8cPaOn3jqoM2fOhDSnNfB6vaqoKNfQ++YoLik1pFmeXVtU8M4yvndgBEpMK5eW2E6DUuNDmlHoKbMpzd+FmqsxMrUGqZ0j1feamKCfv9cdYcscSao6VxnS81ujuKRUdUpJC2kGL+PBJFzYCwAAjESJAQAARqLEAAAAI1FiAACAkSgxAADASJQYAABgJEoMAAAwEiUGAAAYiRIDAACMRIkBAABGosQAAAAjUWIAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACNRYgAAgJEoMQAAwEiUGAAAYCRKDAAAMBIlBgAAGIkSAwAAjESJAQAARqLEAAAAI1FiAACAkSgxAADASJQYAABgJEoMAAAwEiUGAAAYiRIDAACM5GiJmT9/voYMGaLY2Fh17dpVEydO1N69e52MBAAADOFoidm4caOmTZumrVu3at26dTp//rzGjh2rs2fPOhkLAAAYINzJP3zt2rW17q9cuVJdu3ZVXl6ebrnlFodSAQAAEzhaYi5WUlIiSerUqVOdj/v9fvn9/sB9n8/XJLkAOKeoqEg7duwIaUZhYaFNaRpHqPla+td3QUJCglJSUmyZhZah2ZSYmpoazZgxQ8OHD9cNN9xQ5z7z58/X3LlzmzgZACfU1FRJknJycpSTk2PLzPP+c7bMsUtFyUlJLmVlZdkyr6V/fdHR7bRnTyFFBgHNpsRMmzZNBQUF+vTTT+vdZ/bs2Zo5c2bgvs/nU3JyclPEA9DUqqslSdffnq2eg0eGNMqza4sK3lmmqqoqG4LZ53x5qSRLA3/2hLr0Sg96Tkv/+iTJ5zmoz5fPldfrpcQgoFmUmEceeUTvvvuuNm3apB49etS7X2RkpCIjI5swGQCnteuUqE4paSHN8HkO2hOmkcR0TQnpa2zpXx9QH0dLjGVZevTRR7VmzRrl5uaqV69eTsYBAAAGcbTETJs2TatWrdLbb7+t2NhYHTt2TJIUHx+v6OhoJ6MBAIBmztH3iVm8eLFKSko0cuRIJSUlBW5/+tOfnIwFAAAM4PjLSQAAAMHgs5MAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACNRYgAAgJEoMQAAwEiUGAAAYCRKDAAAMBIlBgAAGIkSAwAAjESJAQAARqLEAAAAI1FiAACAkSgxAADASJQYAABgJEoMAAAwEiUGAAAYiRIDAACMRIkBAABGosQAAAAjUWIAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEYKdzpAc+Z2u+X1ekOek5CQoJSUFBsS2a+islKlpaUhzqiwKU3rYce6+/1+m9I0b+WnjumUe29IM856PZKksmK3TrVvZ8ssOKOwsDDkGX6/X5GRkTaksXeWnT8r7Pr5JTXvn2GUmHq43W5lpKepvKIy5FntoqNUuGdvszoIzp8/J0kq+rZIESWHQppV9G3V/59ZFXKuls7OdT965Lv1tiwr5FzNkbesSmGS9q19TfvWvhbyvDBJ+ateCHnOhVmVvlO2zMLVqSg5KcmlrKys0Ie5XJJd3zc2zoqObqc9ewpD/lnhdruVnp6hioryZpWrMVBi6uH1elVeUanXHxiojKSYoOcUesqUtSxfXq+3WR0AVdXVkqToDgnq2LNrSLOiTx2TdFRV1ZSYK7Fz3SNP/E1SsVpmhZFK/dWqkTRvQpLSe3YLadaGXUe0+JMTtsza6z6hnHePqKqyLKQ5aJjz5aWSLA382RPq0is96DmeXVtU8M6ykOfYPcvnOajPl8+15WeF1+tVRUW5ht43R3FJqc0mV2OgxFxBRlKMBqXGOx2j0bQJj1BEVGin18PC29qUpvWwZd3btI5v39TOkep7TfD/IyFJe90Rts06d7YkpOcjNDFdU9QpJS3o5/s8B22ZY/esxhCXlNosc9mJC3sBAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACNRYgAAgJEoMQAAwEiUGAAAYCRKDAAAMBIlBgAAGIkSAwAAjESJAQAARqLEAAAAI1FiAACAkSgxAADASJQYAABgJEoMAAAwEiUGAAAYiRIDAACMRIkBAABGosQAAAAjUWIAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACM1ixKzaNEipaamKioqSkOHDtUXX3zhdCQAANDMOV5i/vSnP2nmzJmaM2eOduzYoR/84AcaN26ciouLnY4GAACaMcdLzIIFCzR16lRNmTJFffv21ZIlS9SuXTstX77c6WgAAKAZC3fyDz937pzy8vI0e/bswLawsDCNGTNGW7ZsuWR/v98vv98fuF9SUiJJ8vl8tmcrKyuTJOUdKlGZvyroOXuPnf1uTl5eYGbQs/butSWTJO3zlEuSdh8pU6V1PKRZ3x4vlSTtOHhGNa7DIc3aWXRakvT5gZM66692fI7ds3YfPvPdP+1Y9+IKSdLXR0t1Ts1jVnPMZPesA0e/+z4uLXar+Jv8kGb5PIckSSVHvlFEuMvxOa1hVnPMJEm+Y25J9v6sOHVor6r8FbbkKisrs/Vn7YVZlmWFNshy0JEjRyxJ1ubNm2ttf/zxx62bb775kv3nzJljSeLGjRs3bty4tYDb4cOHQ+oRjp6JaajZs2dr5syZgfs1NTU6deqUOnfuLJcrtBZ8MZ/Pp+TkZB0+fFhxcXG2zkb9WHdnsO7OYN2bHmvujIvX3bIslZaWqnv37iHNdbTEJCQkqE2bNjp+vPbp3ePHjysxMfGS/SMjIxUZGVlrW4cOHRozouLi4jjQHcC6O4N1dwbr3vRYc2d8f93j4+NDnufohb1t27bV4MGDtX79+sC2mpoarV+/XpmZmQ4mAwAAzZ3jLyfNnDlT2dnZuummm3TzzTdr4cKFOnv2rKZMmeJ0NAAA0Iw5XmL++Z//WSdOnNCvfvUrHTt2TAMHDtTatWvVrVs3R3NFRkZqzpw5l7x8hcbFujuDdXcG6970WHNnNNa6uywr1N9vAgAAaHqOv9kdAABAMCgxAADASJQYAABgJEoMAAAwUqssMfPnz9eQIUMUGxurrl27auLEiYHPmricP//5z0pPT1dUVJT69++v9957rwnSthzBrPvKlSvlcrlq3aKiopooccuwePFiDRgwIPAmU5mZmXr//fcv+xyO9dA1dN051u33/PPPy+VyacaMGZfdj+PdXlez7nYd762yxGzcuFHTpk3T1q1btW7dOp0/f15jx47V2bNn633O5s2b9S//8i+6//779eWXX2rixImaOHGiCgoKmjC52YJZd+m7d3j0eDyB26FDh5ooccvQo0cPPf/888rLy9P27ds1evRo3Xnnndq9e3ed+3Os26Oh6y5xrNtp27ZtWrp0qQYMGHDZ/Tje7XW16y7ZdLyH9MlLLURxcbElydq4cWO9+/z0pz+1JkyYUGvb0KFDrQcffLCx47VYV7PuK1assOLj45suVCvRsWNH67//+7/rfIxjvfFcbt051u1TWlpq9enTx1q3bp01YsQI67HHHqt3X453+zRk3e063lvlmZiLlZSUSJI6depU7z5btmzRmDFjam0bN26ctmzZ0qjZWrKrWXfpu4+A79mzp5KTk6/4f7K4vOrqaq1evVpnz56t96M9ONbtdzXrLnGs22XatGmaMGHCJcdxXTje7dOQdZfsOd4df8dep9XU1GjGjBkaPny4brjhhnr3O3bs2CXvItytWzcdO3assSO2SFe77mlpaVq+fLkGDBigkpISvfjiixo2bJh2796tHj16NGFis+3atUuZmZmqrKxUTEyM1qxZo759+9a5L8e6fRqy7hzr9li9erV27Nihbdu2XdX+HO/2aOi623W8t/oSM23aNBUUFOjTTz91OkqrcrXrnpmZWev/XIcNG6aMjAwtXbpUTz/9dGPHbDHS0tKUn5+vkpIS/eUvf1F2drY2btxY7w9U2KMh686xHrrDhw/rscce07p167gougkFs+52He+tusQ88sgjevfdd7Vp06YrNr/ExEQdP3681rbjx48rMTGxMSO2SA1Z94tFREToxhtv1P79+xspXcvUtm1bXXfddZKkwYMHa9u2bXr55Ze1dOnSS/blWLdPQ9b9YhzrDZeXl6fi4mINGjQosK26ulqbNm3Sq6++Kr/frzZt2tR6Dsd76IJZ94sFe7y3ymtiLMvSI488ojVr1ujjjz9Wr169rviczMxMrV+/vta2devWXfb1bdQWzLpfrLq6Wrt27VJSUlIjJGw9ampq5Pf763yMY73xXG7dL8ax3nC33nqrdu3apfz8/MDtpptu0qRJk5Sfn1/nD1KO99AFs+4XC/p4D/nSYAM99NBDVnx8vJWbm2t5PJ7Arby8PLDP5MmTrVmzZgXuf/bZZ1Z4eLj14osvWoWFhdacOXOsiIgIa9euXU58CUYKZt3nzp1rffDBB9aBAwesvLw86+6777aioqKs3bt3O/ElGGnWrFnWxo0braKiIuurr76yZs2aZblcLuvDDz+0LItjvbE0dN051hvHxb8lw/HeNK607nYd763y5aTFixdLkkaOHFlr+4oVK3TvvfdKktxut8LC/n6iatiwYVq1apV++ctf6sknn1SfPn301ltvXfaiVNQWzLqfPn1aU6dO1bFjx9SxY0cNHjxYmzdv5lqOBiguLtY999wjj8ej+Ph4DRgwQB988IFuu+02SRzrjaWh686x3jQ43p3RWMe7y7Isy+6wAAAAja1VXhMDAADMR4kBAABGosQAAAAjUWIAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgOgUblcLr311lshzbj33ns1ceLEy+4zcuRIzZgx47L7rFy5Uh06dAgpC4DmgxIDtFAnTpzQQw89pJSUFEVGRioxMVHjxo3TZ5995limH/7wh/rXf/3XWtuWLFkil8ullStX1tp+77336h//8R8lSS+//PIlj19JamqqFi5cGFROn8+np556Sunp6YqKilJiYqLGjBmjN998U7zJOdB8tMrPTgJag5/85Cc6d+6cXnvtNV177bU6fvy41q9fr5MnTzqWadSoUVqzZk2tbRs2bFBycrJyc3MDn6ElSbm5ucrOzpYkxcfHN1nGM2fO6B/+4R9UUlKiZ555RkOGDFF4eLg2btyo//iP/9Do0aM5mwM0F7Z8XCWAZuX06dOWJCs3N/ey+9x///1WQkKCFRsba40aNcrKz88PPD5nzhzrBz/4gbVkyRKrR48eVnR0tHXXXXdZZ86cCezzxRdfWGPGjLE6d+5sxcXFWbfccouVl5dX68+RZK1Zs8ayLMv64IMPLEmWx+MJPN6tWzdr0aJFVs+ePQPbvv32W0uStWHDBsuyLCs7O9u68847A4+XlZVZkydPttq3b28lJiZaL774Yq1PzR0xYoQlqdbNsixrxYoVVnx8vLV27VorPT3dat++vTVu3Djr6NGjgdkPPfSQ1b59e+vIkSOXrFlpaal1/vx5y7Isq2fPntbTTz8dyJGSkmK9/fbbVnFxsfVP//RPVvv27a3+/ftb27Ztq/e/AYDQ8HIS0ALFxMQoJiZGb731lvx+f5373HXXXSouLtb777+vvLw8DRo0SLfeeqtOnToV2Gf//v1644039Ne//lVr167Vl19+qYcffjjweGlpqbKzs/Xpp59q69at6tOnj8aPH6/S0tI6/8zhw4crIiJCGzZskCR9/fXXqqio0P3336+TJ0+qqKhI0ndnZ6KiopSZmVnnnMcff1wbN27U22+/rQ8//FC5ubnasWNH4PE333xTPXr00Lx58+TxeOTxeAKPlZeX68UXX9Tvf/97bdq0SW63W//+7/8uSaqpqdHq1as1adIkde/evc51DQ//+wnsl156ScOHD9eXX36pCRMmaPLkybrnnnuUlZWlHTt2qHfv3rrnnnt4CQpoLE63KACN4y9/+YvVsWNHKyoqyho2bJg1e/Zsa+fOnZZlWdYnn3xixcXFWZWVlbWe07t3b2vp0qWWZX13JqZNmzbW3/72t8Dj77//vhUWFlbrTMr3VVdXW7GxsdZf//rXwDZ970yMZVnW8OHDrQceeMCyLMtatGiRNX78eMuyLGvs2LHW8uXLLcuyrMmTJ1ujRo0KPOf7Z2JKS0uttm3bWm+88Ubg8ZMnT1rR0dGBMzGW9d2ZkpdeeqlWvhUrVliSrP379we2LVq0yOrWrZtlWZZ1/PhxS5K1YMGCOr++7+vZs6eVlZUVuO/xeCxJVk5OTmDbli1bLjnzBMA+nIkBWqif/OQnOnr0qN555x3dfvvtys3N1aBBg7Ry5Urt3LlTZWVl6ty5c+CsTUxMjIqKinTgwIHAjJSUFF1zzTWB+5mZmaqpqdHevXslScePH9fUqVPVp08fxcfHKy4uTmVlZXK73fXmGjlypHJzcyV9d93LyJEjJUkjRoyotX3UqFF1Pv/AgQM6d+6chg4dGtjWqVMnpaWlXdW6tGvXTr179w7cT0pKUnFxsSQ1+IzJgAEDAv/erVs3SVL//v0v2XZhPgB7cWEv0IJFRUXptttu02233aacnBz9/Oc/15w5c/Twww8rKSkpUBq+ryEXrWZnZ+vkyZN6+eWX1bNnT0VGRiozM1Pnzp2r9zmjRo3Ss88+qyNHjig3NzfwUs6IESO0dOlSHThwQIcPH9bo0aMb+uVelYiIiFr3XS5XoLx06dJFHTp00J49exo8y+Vy1butpqYmpMwA6saZGKAV6du3r86ePatBgwbp2LFjCg8P13XXXVfrlpCQENjf7Xbr6NGjgftbt25VWFhY4KzHZ599punTp2v8+PHq16+fIiMj5fV6L5th2LBhatu2rX7729+qsrJSgwcPliQNGTJEJ06c0PLly9W+fXvdfPPNdT6/d+/eioiI0Oeffx7Ydvr0ae3bt6/Wfm3btlV1dXWD1icsLEx33323/vCHP9T6ui8oKytTVVVVg2YCaDyUGKAFOnnypEaPHq3XX39dX331lYqKivTnP/9Z//mf/6k777xTY8aMUWZmpiZOnKgPP/xQBw8e1ObNm/XUU09p+/btgTlRUVHKzs7Wzp079cknn2j69On66U9/qsTERElSnz599Pvf/16FhYX6/PPPNWnSJEVHR182W3R0tH74wx/qlVde0fDhw9WmTRtJ35WO72+/+IzJBTExMbr//vv1+OOP6+OPP1ZBQYHuvfdehYXV/ussNTVVmzZt0pEjR65YrL7v2WefVXJysoYOHar//d//1ddff61vvvlGy5cv14033qiysrKrngWgcfFyEtACxcTEaOjQoXrppZd04MABnT9/XsnJyZo6daqefPJJuVwuvffee3rqqac0ZcoUnThxQomJibrlllsC13FI0nXXXacf//jHGj9+vE6dOqU77rhDv/3tbwOP/8///I8eeOABDRo0SMnJyXruuecCLw9dzqhRo7Rp06bA9TAXjBgxQhs2bKj3epgLfvOb36isrEw/+tGPFBsbq3/7t39TSUlJrX3mzZunBx98UL1795bf77/q6106deqkrVu36vnnn9czzzyjQ4cOqWPHjurfv79+85vfNOl71gC4PJfV0CvZALQKv/71r/XWW28pPz/f6SgAUCdeTgIAAEaixAAAACPxchIAADASZ2IAAICRKDEAAMBIlBgAAGAkSgwAADASJQYAABiJEgMAAIxEiQEAAEaixAAAACP9P3m5Pn9fCqjHAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['SepalWidthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['SepalWidthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的萼片更宽，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：9.282772555558111\n",
      "p值：4.362239016010214e-15\n"
     ]
    }
   ],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"SepalWidthCm\"], iris_versicolor[\"SepalWidthCm\"])\n",
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析花瓣长度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 花瓣长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['PetalLengthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['PetalLengthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花花瓣长度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花花瓣长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的花瓣更长，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-39.46866259397272\n",
      "p值：5.717463758170621e-62\n"
     ]
    }
   ],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"PetalLengthCm\"], iris_versicolor[\"PetalLengthCm\"])\n",
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花花瓣长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析花瓣宽度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 花瓣宽度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['PetalWidthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['PetalWidthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的花瓣更宽，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-34.01237858829048\n",
      "p值：4.589080615710866e-56\n"
     ]
    }
   ],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"PetalWidthCm\"], iris_versicolor[\"PetalWidthCm\"])\n",
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过推论统计学的计算过程，我们发现，Setosa鸢尾花和Versicolor鸢尾花萼片、花瓣的长度和宽度平均值，均存在具有统计显著性的差异。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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